Software Product Line Analysis Using Variability-aware Datalog

Autor: Marsha Chechik, Ramy Shahin, Murad Akhundov
Rok vydání: 2021
Předmět:
DOI: 10.36227/techrxiv.14870187.v1
Popis: Applying program analyses to Software Product Lines (SPLs) has been a fundamental research problem at the intersectionof Product Line Engineering and software analysis. Different attempts have been made to "lift" particular product-level analyses to run on the entire product line. In this paper, we tackle the class of Datalog-based analyses (e.g., pointer and taint analyses), study the theoretical aspects of lifting Datalog inference, and implement a lifted inference algorithm inside the Souffl Datalog engine. We evaluate our implementation on a set of Java and C-language benchmark product lines. We show significant savings in processing time and fact database size (billions of times faster on one of the benchmarks) compared to brute-force analysis of each product individually.
Databáze: OpenAIRE